Lead Software Engineer-Golang

JPMorgan Chase & Co.; Bengaluru; On-site; INR 2,500,000 - 4,800,000; Full time

Job summary

JPMorgan Chase & Co. in Bengaluru seeks a Lead Software Engineer to join the Infrastructure Platforms team, delivering trusted, scalable technology while ensuring security and stability.

You will contribute as a core technical member across multiple functions, driving design, development, and operations in a fast-paced agile setting. The role emphasizes cloud-native solutions with Kubernetes, Golang/Java services, secure coding, and AI-assisted engineering practices to accelerate delivery and

Qualifications

• 5+ years of hands-on software engineering experience with system design.
• Experience delivering cloud-native solutions with Kubernetes.
• Proficient in secure SDLC and AI-assisted development tools.

Responsibilities

• Develop and troubleshoot software solutions across multiple domains.
• Build and operate cloud-native solutions using Kubernetes on AWS/GCP/Azure.
• Develop services in Golang and/or Java.
• Ensure secure, high-quality production code via best practices.
• Lead code reviews and enforce validation standards.
• Advise on AI-assisted coding, testing, and incident analysis.

Skills

Programming languages

AI tooling

Cloud native

CI/CD

Tools

Kubernetes

Cloud platforms

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Infrastructure Platforms team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Build and operate cloud-native solutions using Kubernetes with strong systems fundamentals, on at least one cloud provider (AWS / GCP / Azure)
• Develop services primarily in Golang and/or Java (either or both)
• Produce secure, high-quality production code aligned to engineering best practices
• Review and debug code written by others while enforcing consistent validation standards (secure coding, peer review, automated testing)
• Drive consistent validation practices across the team to improve overall code quality and delivery outcomes
• Promote reuse of effective patterns and scalable approaches across the team to improve engineering efficiency
• Identify and implement opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability, and lead evaluation sessions with external vendors/startups and internal teams to assess architectural designs and technical fit within existing systems and information architecture
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Demonstrated experience leading effective use of approved AI‑assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In‑depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience

Preferred qualifications, capabilities, and skills

• Spec Drive Development (SDD) experience is a plus
• Strong AI tool usage fluency (comfortable leveraging AI tools in day‑to‑day engineering workflows)
• Prior understanding of Cloud Governance is a plus